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This paper enhances our understanding of how national culture impacts manufacturing performance (assembly speed, consistency between teams, etc.) during a production process move. The authors also investigate the efficacy of co-location as a strategy to enhance knowledge transfer from one organization to another.

To study the impact of national culture on production process moves, the authors develop and employ a team-based behavioral experiment within and between an individualist society (the United States) and a collectivist one (China). The authors also examine the impact of co-location on knowledge transfer effectiveness within and between these two unique cultures.

Interestingly, co-location has little impact on the performance of US recipient teams. Without co-location, Chinese recipient team performance lags significantly behind the US teams. However, firms can overcome these knowledge transfer challenges by co-locating source and recipient team members. These results suggest that firms should assess the national cultural context when considering co-location to manage their production move. There are contexts where co-location may be incredibly useful to facilitate an effective knowledge transfer (e.g. collectivist cultures like China) and contexts where this approach may not be as valuable (e.g. individualistic cultures such as the United States).

This research contributes to the academic literature in several ways. First, while past research demonstrates that national culture can be an essential barrier to information and knowledge sharing, this paper extends these findings showing that co-location may effectively overcome this barrier. After the authors offer and test the merits of co-location, they also establish the boundary conditions of this approach by showing that the effect of co-location on knowledge transfer is contingent on the cultural context. This contribution enhances our understanding of the relationship between national culture and knowledge sharing and has implications for managers developing approaches to transfer knowledge between cultures. Second, the authors develop and execute a novel cross-country experimental design. While cross-country experiments have been done before (e.g. Ozer et al. 2014, Kuwabara et al. 2007, etc.), it is still rare to see such experiments due to them being “technically difficult and costly” (Ozer et al. 2014, p. 2437). This research not only offer insights into how teams of people from individualist and collectivist societies send, receive and comprehend production knowledge. It also documents how these teams convert this knowledge into production results.

This paper investigates the impact of financial stress on the dynamic connectedness and hedging for oil market and stock-bond markets of the Gulf Cooperation Council (GCC).

This study uses the wavelet coherence model to examine the interactions between financial stress, oil and GCC stock and bond markets. Second, the authors apply the time–frequency connectedness developed by Barunik and Krehlik (2018) so as to identify the direction and scale connectedness among these markets. Third, the authors examine the optimal weights, hedge ratio and hedging effectiveness for oil and financial markets based on constant conditional correlation (CCC), dynamic conditional correlation (DCC) and Baba-Engle-Kraft-Kroner (BEKK)-GARCH models.

The authors have found that the correlation between the oil and stock-bond markets tends to be stable in nonshock periods, but it evolves during oil and financial shocks at lower frequencies. Moreover, the authors find that the oil market and financial stress are the main transmitters of risks. The connectedness is mainly driven by the long term, demonstrating that the markets rapidly process the financial stress spillover effect, and the shock is transmitted over the long run. Optimal weights show different patterns for each negative and positive case of the financial stress index. In the negative (positive) financial stress case, investors should have more oil (stocks) than stocks (oil) in their portfolio in order to minimize risk.

This study has gone some way toward enhancing one’s understanding of the time–frequency connectedness between the financial stress, oil and GCC stock-bond markets. Second, it identifies the impact of financial stress into hedging strategies offering important insights for investors aiming at managing and reducing portfolio risk.

In this study, the authors assess the current state of lean product development and the lean production shop floor, along with the impact of the former on process quality and the latter on product quality and customer complaint reduction. The interplay between process and product quality and customer complaint reduction is assessed, along with their impacts on business performance.

Data were collected from 377 managers working at auto-component manufacturing firms in India. Confirmatory factor analysis was used for scale validation, and structural equation modelling was employed to test the research hypotheses.

The results of the statistical analyses reveal the positive influence of a lean production shop floor on process quality and lean product development on product quality and customer complaint reduction, and thereby on business performance.

The findings of this research provide insights into the interplay between lean and quality factors and their influence on customer complaint reduction and business performance. Practitioners can use the proposed model to strategically design unique products and improve the efficiency and effectiveness of the production shop floor, which can help enhance the product and process quality. This can reduce customer dissatisfaction and improve the business performance.

Few studies have simultaneously investigated the influence of lean product development and lean production shop floors in the Indian manufacturing context. To the best of our knowledge, this study is one of the first attempts to include customer complaint reduction as a construct in a lean model. It helps identify and prioritise the enablers of business performance and provides valuable insights for practitioners to strengthen lean implementation to attain a competitive edge.

This study aims to explain customer reactions to a double deviation by examining the moderating role of prior trust in peer-to-peer (P2P) accommodation platforms on the relationship between perceived betrayal and negative outcomes such as negative word-of-mouth (NWOM), vindictive complaining and patronage reduction.

An online survey was used to obtain a sample of 246 respondents familiar with P2P accommodation platforms. The model was tested using SmartPLS.

The results showed a positive correlation between perceived betrayal and NWOM, vindictive complaining and patronage reduction. Unexpectedly, prior trust had positive moderating effects. High levels of prior trust caused more negative customer reactions than low levels of prior trust.

The findings of this study caution firms about the potential risks to rely on the forgiveness and tolerance of highly trusted customers who may retaliate fiercely to double deviations.

This research unveils the prior trust paradox. Customers' prior trust magnified the negative impact of double-deviation experiences. This study contributes to the service-recovery literature by questioning the buffer effect of prior trust in the context of a double deviation.

This paper investigates the predictive impact of Financial Stress on hedging between the oil market and the GCC stock and bond markets from January 1, 2007, to December 31, 2020. The authors also compare the hedging performance of in-sample and out-of-sample analyses.

For the modeling purpose, the authors combine the GARCH-BEKK model with the machine learning approach to predict the transmission of shocks between the financial markets and the oil market. The authors also examine the hedging performance in order to obtain well-diversified portfolios under both Financial Stress cases, using a One-Dimensional Convolutional Neural Network (1D-CNN) model.

According to the results, the in-sample analysis shows that investors can use oil to hedge stock markets under positive Financial Stress. In addition, the authors prove that oil hedging is ineffective in reducing market risks for bond markets. The out-of-sample results demonstrate the ability of hedging effectiveness to minimize portfolio risk during the recent pandemic in both Financial Stress cases. Interestingly, hedgers will have a more efficient hedging performance in the stock and oil market in the case of positive (negative) Financial Stress. The findings seem to be confirmed by the Diebold-Mariano test, suggesting that including the negative (positive) Financial Stress in the hedging strategy displays better out-of-sample performance than the in-sample model.

This study improves the understanding of the whole sample and positive (negative) Financial Stress estimates and forecasts of hedge effectiveness for both the out-of-sample and in-sample estimates. A portfolio strategy based on transmission shock prediction provides diversification benefits.

This study aims to examine the association between shared transformational leadership and workplace spirituality in teams. While articulating its theoretical propositions, this research draws on the theory of motivational effects of charismatic leadership based on the self-concept.

The paper has adopted the quantitative method and cross-sectional research design while examining the study’s variables’ multi-level relationship. The authors researched 141 project teams in India’s information technology setting.

This study shows that shared transformational leadership is associated with workplace spirituality. This research has also found significant within-team variance in team members’ workplace spirituality experiences.

The study’s results show that the information technology companies’ employees aspire to cultivate individual-specific meaning at work. Therefore, team leaders should strive to display transformational leadership behaviours to build individual-specific meaning and a sense of community among team members.

The study’s findings imply that shared transformational leadership can reduce individualistic utilitarianism and the resulting baneful impact of hedonism. Society can also benefit from shared leadership’s impact on individuals’ self-work integration as it will probably strengthen the “other-benefitting” behaviour instead of mere hedonistic orientation.

This paper has addressed the theoretical tensions regarding the role of shared transformational leadership in inducing employees’ inner life, meaning at work and sense of community. This paper helps us understand shared transformational leadership’s effects on individual workplace spirituality experiences.

Exploration and exploitation have long been documented as prominent approaches to business management and organizational adaptation to external environment. Maintaining balance between these activities is a key to survival and prosperity. However, there is little direct evidence of the effect of such combined usage of both approaches on firm performance in times of crisis, especially within small- and medium-sized enterprises (SMEs). The purpose of this paper is to reveal the role of balanced ambidexterity in shaping firm performance during COVID-19 recession.

Based on a survey of 333 Russian SMEs, the authors test the proposed theoretical framework linking innovative ambidexterity to firm performance level and variability taking into account technological uncertainty.

The results show that innovative ambidexterity tends to increase level and decrease variability of performance outcomes, whereas technological uncertainty acts as a positive contingency for this impact.

The results provide an improved understanding of ambidexterity and organizational literatures by clarifying the contingent nature of the ambidexterity–firm performance relationship during COVID-19 recession.

The study focuses on examining the impact of the supply shock on the Indian macroeconomic variables during the COVID-19 period.

Time-varying factor augmented vector autoregressive model has been employed to study the asymmetry in transmission of supply shock on Indian economy during pre- and post-COVID-19 times.

The authors find that with supply shock, retail food inflation outpaced in COVID-19 times. Production levels reported by IIP fell to abysmally low levels in the post-COVID-19 times when the economy stalled. The liquidity stimulus provided by the central bank led to the negative response of policy rates to the supply shocks during the COVID-19 times.

The study stands novel in examining the impact of COVID-19 pandemic on Indian economy through the lenses of asymmetric transmission of supply shock during pre- and post-COVID-19 times.

Kriging surrogate model has demonstrated a powerful ability to be applied to a variety of engineering challenges by emulating time-consuming simulations. However, when it comes to problems with high-dimensional input variables, it may be difficult to obtain a model with high accuracy and efficiency due to the curse of dimensionality. To meet this challenge, an improved high-dimensional Kriging modeling method based on maximal information coefficient (MIC) is developed in this work.

The hyperparameter domain is first derived and the dataset of hyperparameter and likelihood function is collected by Latin Hypercube Sampling. MIC values are innovatively calculated from the dataset and used as prior knowledge for optimizing hyperparameters. Then, an auxiliary parameter is introduced to establish the relationship between MIC values and hyperparameters. Next, the hyperparameters are obtained by transforming the optimized auxiliary parameter. Finally, to further improve the modeling accuracy, a novel local optimization step is performed to discover more suitable hyperparameters.

The proposed method is then applied to five representative mathematical functions with dimensions ranging from 20 to 100 and an engineering case with 30 design variables.

The results show that the proposed high-dimensional Kriging modeling method can obtain more accurate results than the other three methods, and it has an acceptable modeling efficiency. Moreover, the proposed method is also suitable for high-dimensional problems with limited sample points.

Evaluating warfighter lethality is a critical aspect of military performance. Raw metrics such as marksmanship speed and accuracy can provide some insight, yet interpreting subtle differences can be challenging. For example, is a speed difference of 300 milliseconds more important than a 10% accuracy difference on the same drill? Marksmanship evaluations must have objective methods to differentiate between critical factors while maintaining a holistic view of human performance.

Monte Carlo simulations are one method to circumvent speed/accuracy trade-offs within marksmanship evaluations. They can accommodate both speed and accuracy implications simultaneously without needing to hold one constant for the sake of the other. Moreover, Monte Carlo simulations can incorporate variability as a key element of performance. This approach thus allows analysts to determine consistency of performance expectations when projecting future outcomes.

The review divides outcomes into both theoretical overview and practical implication sections. Each aspect of the Monte Carlo simulation can be addressed separately, reviewed and then incorporated as a potential component of small arms combat modeling. This application allows for new human performance practitioners to more quickly adopt the method for different applications.

Performance implications are often presented as inferential statistics. By using the Monte Carlo simulations, practitioners can present outcomes in terms of lethality. This method should help convey the impact of any marksmanship evaluation to senior leadership better than current inferential statistics, such as effect size measures.